Omar Hasmila A, Domingos Joao S, Patra Arijit, Leeson Paul, Noble J Alison
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:1128-1131. doi: 10.1109/EMBC.2018.8512537.
Analysis of wall motion abnormality using echocardiography is an established method for detecting myocardial ischemia. We describe a hybrid approach of enhancing 2D+T echo datasets with border detection and Eulerian motion magnification to improve the visual assessment of wall motion. We implemented a local phase-based approach using the monogenic signal and its derived features, either feature asymmetry (FA) or oriented feature symmetry (OFS), to detect boundaries of the heart structure. We enhanced the 2D+T datasets using either an intensity-based or phase-based Eulerian Motion Magnification (EMM) video processing technique, and identified among eight different types of enhancements the best performing method as OFS with an accuracy of 78% versus the original B-Mode with an accuracy of 71%.
使用超声心动图分析壁运动异常是检测心肌缺血的一种既定方法。我们描述了一种混合方法，通过边界检测和欧拉运动放大来增强二维加时间（2D+T）回声数据集，以改善壁运动的视觉评估。我们使用单基因信号及其派生特征（特征不对称性（FA）或定向特征对称性（OFS））实施了一种基于局部相位的方法来检测心脏结构的边界。我们使用基于强度或基于相位的欧拉运动放大（EMM）视频处理技术增强了2D+T数据集，并在八种不同类型的增强方法中确定，表现最佳的方法是OFS，准确率为78%，而原始B模式的准确率为71%。
